Understanding quantitative structure-property relationships uncertainty in environmental fate modeling
(2013) In Environmental Toxicology and Chemistry 32(5). p.1069-1076- Abstract
- In cases in which experimental data on chemical-specific input parameters are lacking, chemical regulations allow the use of alternatives to testing, such as in silico predictions based on quantitative structureproperty relationships (QSPRs). Such predictions are often given as point estimates; however, little is known about the extent to which uncertainties associated with QSPR predictions contribute to uncertainty in fate assessments. In the present study, QSPR-induced uncertainty in overall persistence (POV) and long-range transport potential (LRTP) was studied by integrating QSPRs into probabilistic assessments of five polybrominated diphenyl ethers (PBDEs), using the multimedia fate model Simplebox. The uncertainty analysis considered... (More)
- In cases in which experimental data on chemical-specific input parameters are lacking, chemical regulations allow the use of alternatives to testing, such as in silico predictions based on quantitative structureproperty relationships (QSPRs). Such predictions are often given as point estimates; however, little is known about the extent to which uncertainties associated with QSPR predictions contribute to uncertainty in fate assessments. In the present study, QSPR-induced uncertainty in overall persistence (POV) and long-range transport potential (LRTP) was studied by integrating QSPRs into probabilistic assessments of five polybrominated diphenyl ethers (PBDEs), using the multimedia fate model Simplebox. The uncertainty analysis considered QSPR predictions of the fate input parameters' melting point, water solubility, vapor pressure, organic carbonwater partition coefficient, hydroxyl radical degradation, biodegradation, and photolytic degradation. Uncertainty in POV and LRTP was dominated by the uncertainty in direct photolysis and the biodegradation half-life in water. However, the QSPRs developed specifically for PBDEs had a relatively low contribution to uncertainty. These findings suggest that the reliability of the ranking of PBDEs on the basis of POV and LRTP can be substantially improved by developing better QSPRs to estimate degradation properties. The present study demonstrates the use of uncertainty and sensitivity analyses in nontesting strategies and highlights the need for guidance when compounds fall outside the applicability domain of a QSPR. Environ. Toxicol. Chem. 2013;32:10691076. (c) 2013 SETAC (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3800084
- author
- Iqbal, M. Sarfraz ; Golsteijn, Laura ; Oberg, Tomas ; Sahlin, Ullrika LU ; Papa, Ester ; Kovarich, Simona and Huijbregts, Mark A. J.
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Nontesting strategy, Fate assessment, Uncertainty analysis, Applicability domain, Polybrominated diphenyl ethers
- in
- Environmental Toxicology and Chemistry
- volume
- 32
- issue
- 5
- pages
- 1069 - 1076
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- wos:000317852700013
- scopus:84876412109
- pmid:23436749
- ISSN
- 0730-7268
- DOI
- 10.1002/etc.2167
- language
- English
- LU publication?
- no
- id
- c89b76f9-f24c-46e7-aba0-3f1adfbcb7c1 (old id 3800084)
- date added to LUP
- 2016-04-01 10:50:08
- date last changed
- 2024-01-07 02:18:27
@article{c89b76f9-f24c-46e7-aba0-3f1adfbcb7c1, abstract = {{In cases in which experimental data on chemical-specific input parameters are lacking, chemical regulations allow the use of alternatives to testing, such as in silico predictions based on quantitative structureproperty relationships (QSPRs). Such predictions are often given as point estimates; however, little is known about the extent to which uncertainties associated with QSPR predictions contribute to uncertainty in fate assessments. In the present study, QSPR-induced uncertainty in overall persistence (POV) and long-range transport potential (LRTP) was studied by integrating QSPRs into probabilistic assessments of five polybrominated diphenyl ethers (PBDEs), using the multimedia fate model Simplebox. The uncertainty analysis considered QSPR predictions of the fate input parameters' melting point, water solubility, vapor pressure, organic carbonwater partition coefficient, hydroxyl radical degradation, biodegradation, and photolytic degradation. Uncertainty in POV and LRTP was dominated by the uncertainty in direct photolysis and the biodegradation half-life in water. However, the QSPRs developed specifically for PBDEs had a relatively low contribution to uncertainty. These findings suggest that the reliability of the ranking of PBDEs on the basis of POV and LRTP can be substantially improved by developing better QSPRs to estimate degradation properties. The present study demonstrates the use of uncertainty and sensitivity analyses in nontesting strategies and highlights the need for guidance when compounds fall outside the applicability domain of a QSPR. Environ. Toxicol. Chem. 2013;32:10691076. (c) 2013 SETAC}}, author = {{Iqbal, M. Sarfraz and Golsteijn, Laura and Oberg, Tomas and Sahlin, Ullrika and Papa, Ester and Kovarich, Simona and Huijbregts, Mark A. J.}}, issn = {{0730-7268}}, keywords = {{Nontesting strategy; Fate assessment; Uncertainty analysis; Applicability domain; Polybrominated diphenyl ethers}}, language = {{eng}}, number = {{5}}, pages = {{1069--1076}}, publisher = {{John Wiley & Sons Inc.}}, series = {{Environmental Toxicology and Chemistry}}, title = {{Understanding quantitative structure-property relationships uncertainty in environmental fate modeling}}, url = {{http://dx.doi.org/10.1002/etc.2167}}, doi = {{10.1002/etc.2167}}, volume = {{32}}, year = {{2013}}, }